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ANaGRAM: A Natural Gradient Relative to Adapted Model for efficient PINNs learning

Fuente: arXiv

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Dettagli Bibliografici
Autori principali:	Schwencke, Nilo, Furtlehner, Cyril
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Artificial Intelligence Numerical Analysis Optimization and Control I.2.8
Accesso online:	Acceder al recurso
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